This paper presents three approaches for including spatial considerations, in terms of continuous areas of old forest, in a long-term forest planning problem with even-flow and inventory constraints. Two of the approa...
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This paper presents three approaches for including spatial considerations, in terms of continuous areas of old forest, in a long-term forest planning problem with even-flow and inventory constraints. Two of the approaches integrate linear programming with simulated annealing into one single solution procedure. Simulated annealing is used for solving the spatial dimension of the problem, while linear programming is used for solving the non-spatial dimension. The third approach uses only simulated annealing for solving the entire management problem. All three approaches are in a case study applied to a landscape consisting of 755 stands in northern Sweden. The results from this case study indicate that the approaches that use both simulated annealing and linear programming produce more effective solutions in terms of net present value and spatial layout for this landscape than the approach that only uses simulated annealing. (C) 2002 Elsevier Science B.V. All rights reserved.
In this paper the ABS algorithm with singular initial matrix is considered and used to construct an active set algorithm for solving the linear programming problem. We prove that this active set algorithm is reduced t...
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In this paper the ABS algorithm with singular initial matrix is considered and used to construct an active set algorithm for solving the linear programming problem. We prove that this active set algorithm is reduced to the simplex algorithm when it starts from a vertex or it meets a vertex.
Constraint programming (CP) has been successful in a number of combinatorial search and discrete optimisation problems. Yet other more traditional approaches, such as Integer programming (IP), can still give a better ...
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Constraint programming (CP) has been successful in a number of combinatorial search and discrete optimisation problems. Yet other more traditional approaches, such as Integer programming (IP), can still give a better performance on the same problem types. Central to IFS success is its reliance an a fast linear programming (LP) solver providing solutions during the search to the corresponding relaxed problems. These solutions are used to guide the search within IP as well as a means of detecting infeasibility and integrality. This paper shows that there is scope also to include LP within the CP framework, in order to similarly guide the CP search. The problems examined here are one for which CP on its own had proved markedly inferior to IP. Hence a hybrid solver based on the CP search and using an LP solver is configured and run on these problems. The outcome shows that using the LP solver within the CP search is a valuable addition to the available search strategies. An improved performance over the CP-only strategies is obtained and, further, comparable results are obtained to those from IF. Overall, CP + LP can be considered as a more robust approach than either CP or IP on their own on a variety of combinatorial search problems.
We analyze the arithmetic complexity of the linear programming feasibility problem over the reals. For the case of polyhedra defined by 2n half-spaces in R-n we prove that the set l((2n,n)), of parameters describing n...
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We analyze the arithmetic complexity of the linear programming feasibility problem over the reals. For the case of polyhedra defined by 2n half-spaces in R-n we prove that the set l((2n,n)), of parameters describing nonempty polyhedra, has an exponential number of limiting hypersurfaces. From this geometric result we obtain, as a corollary, the existence of a constant c > I Such that, if dense or sparse representation is used to code polynomials, the length of any quantifier-free formula expressing the set l((2n,n)) is bounded from below by Omega(c(n)). Other related complexity results are stated;in particular, a lower bound for algebraic computation trees based oil the notion of limiting hypersurface is presented. (C) 2008 Elsevier Inc. All rights reserved.
In this paper, a linear programming embedded simulated annealing algorithm for solving a comprehensive model in the design and operation of distributed layout -based manufacturing systems is presented. The mathematica...
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In this paper, a linear programming embedded simulated annealing algorithm for solving a comprehensive model in the design and operation of distributed layout -based manufacturing systems is presented. The mathematical model considered incorporates a number of important manufacturing attributes. These attributes include demand fluctuation, system reconfiguration, lot splitting, work load balancing, alternative routing, machine capability, tooling requirements, material handling cost, machine relocation cost, setup cost, inventory carrying cost, in-house production, and subcontracting costs. Optimal solutions for such comprehensive mathematical models can only be found for small size problems due to NP-complexity. To solve the model for large size problems, efficient meta-heuristic algorithm is required. The development of such an algorithm is the main contribution of this paper. Numerical examples are presented to demonstrate the computational performance of the developed algorithm and illustrate a challenge that may be encountered when one tries to embed a linear programming in a metaheuristic.
The author presents a bad-data identification procedure for linear programming (LP) power system static state estimation. LP state estimators minimize the weighted sum of the absolute values of the measurement residua...
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The author presents a bad-data identification procedure for linear programming (LP) power system static state estimation. LP state estimators minimize the weighted sum of the absolute values of the measurement residuals. The proposed procedure first detects the bad data using the measurement residuals of those measurements rejected by the LP estimator. Then the bad measurement is identified and eliminated by estimating the measurement errors of the zero residual measurements. The residuals obtained from this second estimation step are made use of for this purpose. In order to minimize the computational burden during the elimination cycles, a fast way of eliminating measurements through weight changing is also presented. The performance of the proposed procedure is tested and the results are presented, using AEP's 14, 30, 57 and 118.< >
A method is proposed for decomposing morphological structuring elements based on integer linear programming. A decomposition problem is formulated into a set of linear constraints, and an optimal decomposition is a so...
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A method is proposed for decomposing morphological structuring elements based on integer linear programming. A decomposition problem is formulated into a set of linear constraints, and an optimal decomposition is a solution to the constraints. obtained by the cutting-plane simplex algorithm. The method has several advantages, It provides a systematic way of decomposing arbitrarily shaped structuring elements. For convex images. factors call he of any size. not restricted to 3 X 3;the candidate set can be freely assigned by the user, and the optimality criteria call be flexible.
Constructional engineering is becoming the key industry in the national economy. But, construction enterprises are lagging far behind those industrial enterprises with refined management and computer integrated manufa...
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Let D, called the domain, be a fixed finite set and let Gamma, called the valued constraint language, be a fixed set of functions of the form f : D-m -> Q U {infinity}, where different functions might have differen...
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Let D, called the domain, be a fixed finite set and let Gamma, called the valued constraint language, be a fixed set of functions of the form f : D-m -> Q U {infinity}, where different functions might have different arity m. We study the valued constraint satisfaction problem parametrized by Gamma, denoted by VCSP(Gamma). These are minimization problems given by n variables and the objective function given by a sum of functions from Gamma, each depending on a subset of the n variables. For example, if D = {0, 1} and Gamma contains all ternary {0,infinity}-valued functions, VCSP(Gamma) corresponds to 3-SAT. More generally, if Gamma contains only {0,infinity}-valued functions, VCSP(Gamma) corresponds to CSP(Gamma). If D = {0, 1} and Gamma contains all ternary {0, 1}-valued functions, VCSP(Gamma) corresponds to Min-3-SAT, in which the goal is to minimize the number of unsatisfied clauses in a 3-CNF instance. Finite-valued constraint languages contain functions that take on only rational values and not infinite values. Our main result is a precise algebraic characterization of valued constraint languages whose instances can be solved exactly by the basic linear programming relaxation (BLP). For a valued constraint language Gamma, BLP is a decision procedure for Gamma if and only if Gamma admits a symmetric fractional polymorphism of every arity. For a finite-valued constraint language Gamma, BLP is a decision procedure if and only if Gamma admits a symmetric fractional polymorphism of some arity, or equivalently, if Gamma admits a symmetric fractional polymorphism of arity 2. Using these results, we obtain tractability of several novel classes of problems, including problems over valued constraint languages that are (1) submodular on arbitrary lattices;(2) k-submodular on arbitrary finite domains;(3) weakly (and hence strongly) tree submodular on arbitrary trees.
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